JoVE - Journal of Visualized Experiments
JoVE Visualize
Contact Us

HPV-ferroptosis related genes as biomarkers to predict the prognosis of cervical cancer

  • 0Clinical Laboratory CenterHospital of Traditional Chinese Medicine, Affiliated to Xinjiang Medical University, Urumqi, 830011, China.
Discover Oncology +

|

September 20, 2024

|

September 20, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

A new prognostic model using HPV-ferroptosis genes accurately predicts cervical cancer survival. This model aids in personalized treatment strategies by identifying patient responses to chemotherapy and immune microenvironment variations.

Area Of Science

  • Oncology
  • Molecular Biology
  • Genetics

Background

  • Ferroptosis is a key predictor of cancer prognosis.
  • Persistent Human Papillomavirus (HPV) infection is a primary cause of cervical cancer.
  • Developing prognostic biomarkers for cervical cancer is crucial for patient outcomes.

Purpose Of The Study

  • To explore the prognostic value of HPV-ferroptosis related genes in cervical cancer.
  • To establish and validate a prognostic model for cervical cancer patients based on these genes.

Main Methods

  • Identified differentially expressed HPV-ferroptosis related genes from the GSE7410 dataset.
  • Selected five key genes (CYBB, VEGFA, CKB, EFNA1, HELLS) with prognostic significance.
  • Utilized multifactorial Cox regression for model construction and validation, alongside drug susceptibility and immune infiltration analyses.

Main Results

  • The prognostic model demonstrated stability and accuracy in both training (TCGA) and validation (GSE44001) sets.
  • Significant differences in overall survival (OS) were observed between high-risk and low-risk groups.
  • Low-risk group showed enhanced T cell costimulation; high-risk group exhibited better response to cisplatin, paclitaxel, docetaxel, and cyclophosphamide.

Conclusions

  • The HPV-ferroptosis related gene prognostic model offers reliable prediction of cervical cancer prognosis.
  • The model provides valuable guidance for clinicians regarding drug sensitivity and immune microenvironment modulation.
  • This approach supports personalized treatment strategies for cervical cancer patients.

Keywords: